Generative Adversarial Networks (GAN)

Generative Adversarial Networks (GANs) are a type of artificial intelligence that involve two neural networks: a generator and a discriminator. The generator creates fake data, like images or music, while the discriminator tries to distinguish between real and fake data. They compete against each other—the generator improves by learning to create more convincing outputs, and the discriminator sharpens its ability to identify fakes. This process continues until the generator produces data that is nearly indistinguishable from real data, showcasing the potential of AI to generate creative content autonomously.